Interest-based content customization

Abstract

A computer-implemented method for customizing training contents for a user, including: establishing a user profile and a personal learning corpus for the user; generating a first baseline indicating that the user is interested and a second baseline indicating that the user is not interested; monitoring the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; comparing the reactions with the first baseline and the second baseline to determine an interest level; and recommending additional contents related to the second topic if the interest level is higher than a predefined threshold.

What is claimed is: 
     
       1. A computer-implemented method for customizing training contents for a user in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor, the method comprising:
 establishing, by the processor, a user profile and a personal learning corpus for the user; 
 generating, by the processor, a first baseline indicating that the user is interested in a first topic and a second baseline indicating that the user is not interested in the first topic, wherein the first baseline and the second baseline are generated based on one or more of biometrical indicators, facial expressions, and body language when the user is consuming contents related to the first topic; 
 monitoring, by the processor, the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; 
 comparing, by the processor, the reactions with the first baseline and the second baseline to determine an interest level; and 
 recommending, by the processor, additional contents related to the second topic if the interest level is higher than a predefined threshold. 
 
     
     
       2. The method of  claim 1 , further comprising:
 adding, by the processor, the recommended contents into the personal learning corpus. 
 
     
     
       3. The method of  claim 1 , further comprising:
 updating, by the processor, the user profile with one or more skills learnt from the recommended contents. 
 
     
     
       4. The method of  claim 1 , wherein the user profile includes contents that the user has viewed and skills that the user has. 
     
     
       5. The method of  claim 4 , wherein the contents that the user has viewed include live presentations, online presentations, online or physical books, online or physical training materials, and emails. 
     
     
       6. The method of  claim 4 , wherein the skills that the user has are revealed in a resume and skill badges. 
     
     
       7. The method of  claim 1 , wherein the biometrical indicators include eye movement and heart rate. 
     
     
       8. A computer program product for customizing training contents for a user, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
 establish a user profile and a personal learning corpus for the user; 
 generate a first baseline indicating that the user is interested in a first topic and a second baseline indicating that the user is not interested in the first topic, wherein the first baseline and the second baseline are generated based on one or more of biometrical indicators, facial expressions, and body language when the user is consuming contents related to the first topic; 
 monitor the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; 
 compare the reactions with the first baseline and the second baseline to determine an interest level; and 
 recommend additional contents related to the second topic if the interest level is higher than a predefined threshold. 
 
     
     
       9. The computer program product as recited in  claim 8 , wherein the processor is further caused to:
 add the recommended contents into the personal learning corpus; and 
 update the user profile with one or more skills learnt from the recommended contents. 
 
     
     
       10. The computer program product as recited in  claim 8 , wherein the user profile includes contents that the user has viewed and skills that the user has. 
     
     
       11. The computer program product as recited in  claim 10 , wherein the contents that the user has viewed include live presentations, online presentations, online or physical books, online or physical training materials, and emails; and the skills that the user has are revealed in a resume and skill badges. 
     
     
       12. The computer program product as recited in  claim 8 , wherein the processor is further caused to:
 identify the user's current level of expertise based on the user profile, and an expected level of expertise based on the user's job title; 
 determine a difference between the user's current level and expected level; and 
 recommend the additional contents based on the difference, so that the user reaches the expected level. 
 
     
     
       13. The computer program product as recited in  claim 8 , wherein the processor is further caused to
 compare the personal learning corpus with other users' personal learning corpora; and 
 adding new contents of the other users' personal learning corpora into the personal learning corpus. 
 
     
     
       14. The computer program product as recited in  claim 13 , wherein the other users have a same job title as the user. 
     
     
       15. A system for customizing training contents for a user, comprising:
 a processor configured to:
 establish a user profile and a personal learning corpus for the user; 
 generate a first baseline indicating that the user is interested in a first topic and a second baseline indicating that the user is not interested in the first topic, wherein the first baseline and the second baseline are established based on one or more of biometrical indicators, facial expressions, and body language when the user is consuming contents related to the first topic; 
 monitor the user's reactions when the user is consuming contents related to a second topic, wherein the reactions include the one or more of biometrical indicators, facial expressions, and body language; 
 compare the reactions with the first baseline and the second baseline to determine an interest level; and 
 recommend additional contents related to the second topic if the interest level is higher than a predefined threshold. 
 
 
     
     
       16. The system as recited in  claim 15 , wherein the processor is further configured to:
 add the recommended contents into the personal learning corpus; and 
 update the user profile with one or more skills learnt from the recommended contents. 
 
     
     
       17. The system as recited in  claim 15 , wherein the user profile includes contents that the user has viewed and skills that the user has, wherein the contents that the user has viewed include live presentations, online presentations, online or physical books, online or physical training materials, and emails; and the skills that the user has are revealed in a resume and skill badges. 
     
     
       18. The system as recited in  claim 15 , wherein the processor is further configured to:
 compare the personal learning corpus with other users' personal learning corpora; and 
 adding new contents of the other users' personal learning corpora into the personal learning corpus. 
 
     
     
       19. The system as recited in  claim 18 , wherein the other users have a same job title as the user. 
     
     
       20. The system as recited in  claim 18 , wherein the other users and the first user joined in a same live presentation.